Baselines:
We compare our approach against both learning and non-learning baseline methods.
Among learning based methods we initially use models that use 3D scene input and output the binary precondition.
We use multiple baseline architectures to represent this learned model.
First, similar to our object relation model, we use a 3D ResNet-18 model with the output being projected down using multiple linear layers to predict the precondition output. To increase the representation capacity of this baseline model we also evaluate a ResNet-34 based model which is adapted in the same way as [1]}.
Given the limited amount of real world data, we also compare against a smaller VGG [2]} based model with 3D convolutions.
